396 results
(View BibTeX file of all listed publications)

**Algorithmic Recourse: from Counterfactual Explanations to Interventions**
*37th International Conference on Machine Learning (ICML)*, July 2020 (conference) Submitted

**Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Online Hybrid Model Predictive Control**
*21rst IFAC World Congress*, July 2020 (conference) Accepted

**A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming**
*21rst IFAC World Congress*, July 2020 (conference) Accepted

**Model-Agnostic Counterfactual Explanations for Consequential Decisions**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, June 2020 (conference) Accepted

**Kernel Conditional Moment Test via Maximum Moment Restriction**
*Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI)*, June 2020 (conference) Accepted

**A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, June 2020 (conference) Accepted

**Kernel Conditional Density Operators**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, Proceedings of Machine Learning Research, June 2020 (conference) Accepted

**A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control**
*2nd Annual Conference on Learning for Dynamics and Control (L4DC)*, June 2020 (conference) Accepted

**Disentangling Factors of Variations Using Few Labels**
*8th International Conference on Learning Representations (ICLR)*, April 2020 (conference)

**Mixed-curvature Variational Autoencoders**
*8th International Conference on Learning Representations (ICLR)*, April 2020 (conference)

**Non-linear interlinkages and key objectives amongst the Paris Agreement and the Sustainable Development Goals**
*ICLR 2020 Workshop "Tackling Climate Change with Machine Learning"*, April 2020 (conference)

**From Variational to Deterministic Autoencoders**
*8th International Conference on Learning Representations (ICLR) *, April 2020, *equal contribution (conference) Accepted

**On Mutual Information Maximization for Representation Learning**
*8th International Conference on Learning Representations (ICLR)*, April 2020 (conference) Accepted

**Towards causal generative scene models via competition of experts**
*ICLR 2020 Workshop "Causal Learning for Decision Making"*, April 2020, *equal contribution (conference)

**More Powerful Selective Kernel Tests for Feature Selection **
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2020 (conference) To be published

**Computationally Tractable Riemannian Manifolds for Graph Embeddings**
*37th International Conference on Machine Learning (ICML)*, 2020 (conference) Submitted

**A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models **
*IEEE International Conference on Robotics and Automation (ICRA)*, 2020 (conference) Accepted

**Practical Accelerated Optimization on Riemannian Manifolds**
*37th International Conference on Machine Learning (ICML)*, 2020 (conference) Submitted

**Fair Decisions Despite Imperfect Predictions**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2020 (conference) Accepted

**Constant Curvature Graph Convolutional Networks**
*37th International Conference on Machine Learning (ICML)*, 2020, *equal contribution (conference) Submitted

**Divide-and-Conquer Monte Carlo Tree Search for goal directed planning**
2020, *equal contribution (conference) Submitted

**Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI**
Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience},
year = {2013},
month = {7},
volume = {14},
number = {Supplement 1},
pages = {A1}, (talk)

**Falsification and future performance**
In *Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence*, 7070, pages: 65-78, Lecture Notes in Computer Science, Springer, Berlin, Germany, Solomonoff 85th Memorial Conference, January 2013 (inproceedings)

**Feedback Error Learning for Rhythmic Motor Primitives**
In *Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA 2013)*, pages: 1317-1322, 2013 (inproceedings)

**Gaussian Process Vine Copulas for Multivariate Dependence**
In *Proceedings of the 30th International Conference on Machine Learning, W&CP 28(2)*, pages: 10-18, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013, Poster:
http://people.tuebingen.mpg.de/dlopez/papers/icml2013_gpvine_poster.pdf (inproceedings)

**The Randomized Dependence Coefficient**
In *Advances in Neural Information Processing Systems 26*, pages: 1-9, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**On a link between kernel mean maps and Fraunhofer diffraction, with an application to super-resolution beyond the diffraction limit**
In *IEEE Conference on Computer Vision and Pattern Recognition*, pages: 1083-1090, IEEE, CVPR, 2013 (inproceedings)

**Output Kernel Learning Methods**
In *International Workshop on Advances in Regularization,
Optimization, Kernel Methods and Support Vector Machines: theory and applications*, ROKS, 2013 (inproceedings)

**Alignment-based Transfer Learning for Robot Models**
In *Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN 2013)*, pages: 1-7, 2013 (inproceedings)

**Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method**
In *13th International Conference on Data Mining*, pages: 1003-1008, (Editors: H. Xiong, G. Karypis, B. M. Thuraisingham, D. J. Cook and X. Wu), IEEE Computer Society, ICDM, 2013 (inproceedings)

**A probabilistic approach to robot trajectory generation**
In *Proceedings of the 13th IEEE International Conference on Humanoid Robots (HUMANOIDS)*, pages: 477-483, IEEE, 13th IEEE-RAS International Conference on Humanoid Robots, 2013 (inproceedings)

**Geometric optimisation on positive definite matrices for elliptically contoured distributions**
In *Advances in Neural Information Processing Systems 26*, pages: 2562-2570, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Fast Probabilistic Optimization from Noisy Gradients**
In *Proceedings of The 30th International Conference on Machine Learning, JMLR W&CP 28(1)*, pages: 62–70, (Editors: S Dasgupta and D McAllester), ICML, 2013 (inproceedings)

**Structure and Dynamics of Information Pathways in On-line Media**
In *6th ACM International Conference on Web Search and Data Mining (WSDM)*, pages: 23-32, (Editors: S Leonardi, A Panconesi, P Ferragina, and A Gionis), ACM, WSDM, 2013 (inproceedings)

**Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments**
In *Proceedings of the Tenth European Workshop on Reinforcement Learning *, pages: 103-116, (Editors: MP Deisenroth and C Szepesvári and J Peters), JMLR, EWRL, 2013 (inproceedings)

**Domain adaptation under Target and Conditional Shift**
In *Proceedings of the 30th International Conference on Machine Learning, W&CP 28 (3)*, pages: 819–827, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013 (inproceedings)

**From Ordinary Differential Equations to Structural Causal Models: the deterministic case **
In *Proceedings of the Twenty-Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence*, pages: 440-448, (Editors: A Nicholson and P Smyth), AUAI Press, Corvallis, Oregon, UAI, 2013 (inproceedings)

**A machine learning approach for non-blind image deconvolution**
In *IEEE Conference on Computer Vision and Pattern Recognition*, pages: 1067-1074, IEEE, CVPR, 2013 (inproceedings)

**Autonomous Reinforcement Learning with Hierarchical REPS**
In *Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN 2013)*, pages: 1-8, 2013 (inproceedings)

**Geometric Tree Kernels: Classification of COPD from Airway Tree Geometry**
In *Information Processing in Medical Imaging*, pages: 171-183, (Editors: JC Gee and S Joshi and KM Pohl and WM Wells and L Zöllei), Springer, Berlin Heidelberg, 23rd International Conference on Information Processing in Medical Imaging (IPMI), 2013, Lecture Notes in Computer Science, Vol. 7017 (inproceedings)

**On estimation of functional causal models: Post-nonlinear causal model as an example**
In *First IEEE ICDM workshop on causal discovery *, 2013, Held in conjunction with the 12th IEEE International Conference on Data Mining (ICDM 2013) (inproceedings)

**Object Modeling and Segmentation by Robot Interaction with Cluttered Environments**
In *Proceedings of the IEEE International Conference on Humanoid Robots (HUMANOIDS)*, pages: 169-176, IEEE, 13th IEEE-RAS International Conference on Humanoid Robots, 2013 (inproceedings)

**Reflection methods for user-friendly submodular optimization**
In *Advances in Neural Information Processing Systems 26*, pages: 1313-1321, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Data-Efficient Generalization of Robot Skills with Contextual Policy Search**
In *Proceedings of the 27th National Conference on Artificial Intelligence (AAAI 2013)*, (Editors: desJardins, M. and Littman, M. L.), AAAI Press, 2013 (inproceedings)

**One-class Support Measure Machines for Group Anomaly Detection**
In *Proceedings 29th Conference on Uncertainty in Artificial Intelligence (UAI)*, pages: 449-458, (Editors: Ann Nicholson and Padhraic Smyth), AUAI Press, Corvallis, Oregon, UAI, 2013 (inproceedings)

**Modeling Information Propagation with Survival Theory**
In *Proceedings of the 30th International Conference on Machine Learning, JMLR W&CP 28 (3)*, pages: 666-674, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013 (inproceedings)

**How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data**
In *Proceedings of the 3rd International Workshop on Pattern Recognition in NeuroImaging (PRNI)*, pages: 102-105, IEEE Xplore Digital Library, PRNI, 2013 (inproceedings)

**Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders **
In *Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI)*, pages: 556-565, (Editors: A Nicholson and P Smyth), AUAI Press Corvallis, Oregon, USA, UAI, 2013 (inproceedings)

**Improving alpha matting and motion blurred foreground estimation**
In *IEEE Conference on Image Processing (ICIP)*, pages: 3446-3450, IEEE, ICIP, 2013 (inproceedings)

**Towards Robot Skill Learning: From Simple Skills to Table Tennis**
In *Machine Learning and Knowledge Discovery in Databases, Proceedings of the European Conference on Machine Learning, Part III (ECML 2013)*, LNCS 8190, pages: 627-631, (Editors: Blockeel, H.,Kersting, K., Nijssen, S., and Zelezný, F.), Springer, 2013 (inproceedings)